Decision Trees

AutoProf at its core is a pipeline building code, as such it has a more advanced feature for constructing complex pipelines: decision trees. In a decision tree pipeline, one can essentially construct a flow chart of decisions and corresponding methods to run and options to use. The beginning of the tree is always ‘head’ and AutoProf will continue to read those steps until it reaches a step containing the word branch (any other text can be included in the step name so you can write many different branches). At a branch step, AutoProf will provide the usual inputs, but the output should be a string or None and a dictionary of new options (if any). If None is returned then AutoProf carries on along the same branch it is already on. If a string is returned, then that is taken as the key from which to check for the next step in the pipeline steps object. An empty dictionary can be used to change no options. When switching branches, AutoProf will start at the beginning of the new branch. Note, the new branch can even be the branch you started on so watch out for infinite loops!

For example, in a large sample, one may wish to process edge-on galaxies differently than the others, but it may not be clear which galaxies fit the edge-on criteria until the photometry is done. In this example, one could have AutoProf perform photometry up to the point of the isophoteinit step, then the rest of the functions could be chosen based on the ellipticity of the initialized ellipse. To make this work one could add:

def My_Edgeon_Fit_Method(IMG, results, options):
    N = 100
    return IMG, {'fit ellip': np.array([results['init ellip']]*N), 'fit pa': np.array([results['init pa']]*N),
                 'fit ellip_err': np.array([0.05]*N), 'fit pa_err': np.array([5*np.pi/180]*N),
                 'fit R': np.logspace(0,np.log10(results['init R']*2),N)}

ap_new_pipeline_methods = {'branch edgeon': lambda IMG,results,options: ('edgeon' if results['init ellip'] > 0.8 else 'standard', {}),
                           'edgeonfit': My_Edgeon_Fit_Method}

ap_new_pipeline_steps = {'head': ['background', 'psf', 'center', 'isophoteinit', 'branch edgeon'],
                         'standard': ['isophotefit', 'isophoteextract', 'checkfit', 'writeprof'],
                         'edgeon': ['edgeonfit', 'isophoteextract', 'writeprof', 'axialprofiles', 'radialprofiles']}

in the config file. This config file would apply a standard pipeline for face-on or moderately inclined galaxies, but a special pipeline for edge-on galaxies which includes a user defined fitting function My_Edgeon_Fit_Method, axial profiles, and radial profiles. This example is included in the test folder as the example config file.